Evidence of spatial genetic structure in a snow leopard population from Gansu, China.

Understanding the spatial structure of genetic diversity provides insights into a populations' genetic status and enables assessment of its capacity to counteract the effects of genetic drift. Such knowledge is particularly scarce for the snow leopard, a conservation flagship species of Central Asia mountains. Focusing on a snow leopard population in the Qilian mountains of Gansu Province, China, we characterised the spatial genetic patterns by incorporating spatially explicit indices of diversity and multivariate analyses, based on different inertia levels of Principal Component Analysis (PCA). We compared two datasets differing in the number of loci and individuals. We found that genetic patterns were significantly spatially structured and were characterised by a broad geographical division coupled with a fine-scale cline of differentiation. Genetic admixture was detected in two adjoining core areas characterised by higher effective population size and allelic diversity, compared to peripheral localities. The power to detect significant spatial relationships depended primarily on the number of loci, and secondarily on the number of PCA axes. Spatial patterns and indices of diversity highlighted the cryptic structure of snow leopard genetic diversity, likely driven by its ability to disperse over large distances. In combination, the species' low allelic richness and large dispersal ability result in weak genetic differentiation related to major geographical features and isolation by distance. This study illustrates how cryptic genetic patterns can be investigated and analysed at a fine spatial scale, providing insights into the spatially variable isolation effects of both geographic distance and landscape resistance.

Spatiotemporal behavior of predators and prey in an arid environment of Central Asia.

The mechanisms of interactions between apex and smaller carnivores may range from competition to facilitation. Conversely, interactions between predators and prey are mainly driven by the prey reducing the likelihood of encounters with predators. In this study, we investigated (1) the spatiotemporal interactions between an apex (the snow leopard) and a meso-predator (the red fox), and (2) the temporal interactions between the snow leopard and its potential prey (Siberian ibex, argali, Asian wild ass, Tolai hare) through camera trapping in the Mongolian Great Gobi-A. The probability of occurrence for the red fox was higher in the presence of the snow leopard than in its absence. Moreover, the red fox activity pattern matched that of the snow leopard, with both species mostly active at sunset. This positive spatiotemporal interaction suggests that the presence of the snow leopard may be beneficial for the red fox in terms of scavenging opportunities. However, other explanations may also be possible. Amongst prey, the Siberian ibex and the argali were mainly active during the day, whereas the Asian wild ass and the Tolai hare were more nocturnal. These findings suggest that potential prey (especially the Siberian ibex and the argali) may shape their behavior to decrease the opportunity for encounters with the snow leopard. Our results have revealed complex interactions between apex and smaller predators and between apex predator and its potential prey.

Anthropogenic pressures increase extinction risk of an isolated Asian elephant (Elephas maximus) population in southwestern China, as revealed by a combination of molecular- and landscape-scale approaches.

Identification of the effect of anthropogenic threats on ecosystem is crucial. We used molecular tools and remote sensing to evaluate the population status of an isolated Asian elephant population in southwestern China in response to changes in habitat suitability between 1989 and 2019. A total of 22 unique genotypes were identified from 117 dung samples collected between March and June 2018 using microsatellite DNA analysis, including 13 males and 9 females. Based on the size of fecal boli, 1 animal was a juvenile, 9 were subadults, and 12 were adults, indicating that recruitment was limited. The effective population size was small (15.3) but there was no signature of a recent population bottleneck. We observed a low genetic diversity (He = 0.46 ± 0.05) and a high level of inbreeding (Fis of 0.43 ± 0.11), suggesting low population viability and high risk of extinction. In total, these elephants lost nearly two thirds (62%) of their habitat in 3 decades. The expansion of agriculture and rubber plantations followed by an increase in human settlements after 1989 increased the isolation of this population. We recommend that resettlement of 800 inhabitants of 2 villages and the abandonment of associated farmland and rubber plantations would make an additional 20 km2 of suitable habitat available. This could allow a population increase of 14 elephants, possibly by translocating individuals from elsewhere in China. Our findings can be applied to the management and conservation of other fragmented populations in China or in other range countries of Asian elephants.

Meta-replication, sampling bias, and multi-scale model selection: A case study on snow leopard (Panthera uncia) in western China.

Replicated multiple scale species distribution models (SDMs) have become increasingly important to identify the correct variables determining species distribution and their influences on ecological responses. This study explores multi-scale habitat relationships of the snow leopard (Panthera uncia) in two study areas on the Qinghai-Tibetan Plateau of western China. Our primary objectives were to evaluate the degree to which snow leopard habitat relationships, expressed by predictors, scales of response, and magnitude of effects, were consistent across study areas or locally landcape-specific. We coupled univariate scale optimization and the maximum entropy algorithm to produce multivariate SDMs, inferring the relative suitability for the species by ensembling top performing models. We optimized the SDMs based on average omission rate across the top models and ensembles' overlap with a simulated reference model. Comparison of SDMs in the two study areas highlighted landscape-specific responses to limiting factors. These were dependent on the effects of the hydrological network, anthropogenic features, topographic complexity, and the heterogeneity of the landcover patch mosaic. Overall, even accounting for specific local differences, we found general landscape attributes associated with snow leopard ecological requirements, consisting of a positive association with uplands and ridges, aggregated low-contrast landscapes, and large extents of grassy and herbaceous vegetation. As a means to evaluate the performance of two bias correction methods, we explored their effects on three datasets showing a range of bias intensities. The performance of corrections depends on the bias intensity; however, density kernels offered a reliable correction strategy under all circumstances. This study reveals the multi-scale response of snow leopards to environmental attributes and confirms the role of meta-replicated study designs for the identification of spatially varying limiting factors. Furthermore, this study makes important contributions to the ongoing discussion about the best approaches for sampling bias correction.

Assessment of habitat suitability of the snow leopard (Panthera uncia) in Qomolangma National Nature Reserve based on MaxEnt modeling.

Habitat evaluation constitutes an important and fundamental step in the management of wildlife populations and conservation policy planning. Geographic information system (GIS) and species presence data provide the means by which such evaluation can be done. Maximum Entropy (MaxEnt) is widely used in habitat suitability modeling due to its power of accuracy and additional descriptive properties. To survey snow leopard populations in Qomolangma (Mt. Everest, QNNR) National Nature Reserve, Tibet, China, we pooled 127 pugmarks, 415 scrape marks, and 127 non-invasive identifications of the animal along line transects and recorded 87 occurrences through camera traps from 2014-2017. We adopted the MaxEnt model to generate a map highlighting the extent of suitable snow leopard habitat in QNNR. Results showed that the accuracy of the MaxEnt model was excellent (mean AUC=0.921). Precipitation in the driest quarter, ruggedness, elevation, maximum temperature of the warmest month, and annual mean temperature were the main environmental factors influencing habitat suitability for snow leopards, with contribution rates of 20.0%, 14.4%, 13.3%, 8.7%, and 8.2% respectively. The suitable habitat area extended for 7001.93 km2, representing 22.72% of the whole reserve. The regions bordering Nepal were the main suitable snow leopard habitats and consisted of three separate habitat patches. Our findings revealed that precipitation, temperature conditions, ruggedness, and elevations of around 4000 m influenced snow leopard preferences at the landscape level in QNNR. We advocate further research and cooperation with Nepal to evaluate habitat connectivity and to explore possible proxies of population isolation among these patches. Furthermore, evaluation of subdivisions within the protection zones of QNNR is necessary to improve conservation strategies and enhance protection.